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Showing 61 - 80 results of 9,815 for search '(( alignment network algorithm ) OR ((( data encoding algorithm ) OR ( data using algorithm ))))', query time: 0.45s Refine Results
  1. 61
    Data design.

    Data design. by Danqiangyu Zhou (22146196)

    Published 2025
    “…The improved decision tree algorithm exhibits consistent performance across varying data volumes, achieving an accuracy exceeding 93% when handling 15,000 to 50,000 sentences, surpassing comparable state-of-the-art algorithms. …”
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  2. 62
    Performance of classifiers for normal and abnormal task detection using Recall (R), Precision (P), and F1-score (F1). G.LSTM, G.DNN, and G.CNN denote proposed models with Noise-Aware Encoder (NAE).

    Performance of classifiers for normal and abnormal task detection using Recall (R), Precision (P), and F1-score (F1). G.LSTM, G.DNN, and G.CNN denote proposed models with Noise-Awa... by Amin Ullah (12015113)

    Published 2025
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  3. 63
    Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  4. 64
    Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  5. 65
    Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx

    Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx by Xuehui Fan (10762662)

    Published 2025
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  6. 66
    Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  7. 67
    Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  8. 68
    Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  9. 69
    Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  10. 70
    Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  11. 71
    Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx

    Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

    Published 2025
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  12. 72
    Precise Discovery of Novel N‑Terminal Proteoforms beyond the Limitations of Proteogenomics and <i>De Novo</i> Sequencing

    Precise Discovery of Novel N‑Terminal Proteoforms beyond the Limitations of Proteogenomics and <i>De Novo</i> Sequencing by Cuitong He (5446760)

    Published 2025
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  13. 73
    Minimal data set definition.

    Minimal data set definition. by Hui Yang (91136)

    Published 2024
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  14. 74
    Mean and standard deviation (SD) of MRI-derived myelin water fraction (MWF) values calculated using the data-driven mcT<sub>2</sub> approach and the conventional approach for the two mice groups and across six brain ROIs: cortex, medial corpus callosum (MCC), external corpus callosum (ECC), hippocampus (HIPP), thalamus, and striatum. All relevant data are available at data-driven-mcT2-cuprizone-validation GitHub repository and can be accessed at: https://github.com/NoamBenEliezer/data-driven-mcT2-cuprizone-validation.

    Mean and standard deviation (SD) of MRI-derived myelin water fraction (MWF) values calculated using the data-driven mcT<sub>2</sub> approach and the conventional approach for the t... by Noam Omer (21402801)

    Published 2025
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  15. 75
    The mAP for all algorithms and 80% of the data used for training.

    The mAP for all algorithms and 80% of the data used for training. by Mohammad Amin Fraiwan (20469541)

    Published 2024
    “…<p>The mAP for all algorithms and 80% of the data used for training.</p>…”
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  16. 76
    The mAP for all algorithms and 50% of the data used for training.

    The mAP for all algorithms and 50% of the data used for training. by Mohammad Amin Fraiwan (20469541)

    Published 2024
    “…<p>The mAP for all algorithms and 50% of the data used for training.</p>…”
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  17. 77
    The mAP for all algorithms and 60% of the data used for training.

    The mAP for all algorithms and 60% of the data used for training. by Mohammad Amin Fraiwan (20469541)

    Published 2024
    “…<p>The mAP for all algorithms and 60% of the data used for training.</p>…”
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  18. 78
    Point cloud data registration using the original ICP algorithm.

    Point cloud data registration using the original ICP algorithm. by Mengyuan Yan (14200322)

    Published 2025
    “…<p>Point cloud data registration using the original ICP algorithm.…”
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  19. 79
    Summary of key parameters used in the CSCAP algorithm.

    Summary of key parameters used in the CSCAP algorithm. by Manxing Shi (22367181)

    Published 2025
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  20. 80
    Features selection using the Boruta algorithm.

    Features selection using the Boruta algorithm. by Nishat Tasnim Thity (21755858)

    Published 2025
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